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Asset Intelligence Manager

Greenacre Recruitment Ltd

Greater London

On-site

GBP 58,000 - 63,000

Full time

10 days ago

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Job summary

A leading housing provider in Greater London is seeking an Asset Intelligence Manager to lead a high-impact team. This pivotal role involves overseeing robust property information systems, enhancing data governance, and ensuring data quality to support strategic planning and compliance. The ideal candidate will have extensive experience in asset/property data management, strong skills in Power BI and Excel, and the ability to effectively lead a team. This position offers a permanent contract with a competitive salary range of £58,899 - £62,106.

Qualifications

  • Extensive technical experience in asset/property data management.
  • Strong database experience, ideally within asset management.
  • Proficiency in data governance tools.

Responsibilities

  • Lead asset data governance and maintain a robust property information framework.
  • Develop and improve asset information systems.
  • Drive high standards of data gathering, validation, QA, and audit readiness.
  • Produce validated reports and portfolio insights.
  • Manage contractors and support asset management system projects.
  • Coach and motivate a multi-disciplinary team.

Skills

Power BI
Excel
Data governance
Database management
GIS (ArcGIS, MapInfo)
Job description
Asset Intelligence Manager (Housing & Property Data)

London

Permanent, £58,899 - £62,106

An exciting opportunity has opened up for an Asset Intelligence Manager to lead a high-impact team for a housing provider in London. This is a pivotal role for someone who loves turning complex property data into clear insight - and who wants their work to directly improve homes, services, and investment decisions for thousands of residents.

The role

As Asset Intelligence Manager, you’ll ensure the organisation has robust, accurate, and accessible property information across a diverse portfolio of socially rented homes and commercial assets. You’ll own data governance, oversee asset information systems, and drive best-practice data quality and integration across the business.

You’ll also lead a specialist Asset Intelligence Team, working closely with internal services and external partners to make sure asset data supports strategic planning, capital programmes, repairs, compliance, and statutory reporting.

What you’ll be doing

You’ll be at the centre of how property intelligence is captured, managed, and used - with responsibilities including :

  • Leading asset data governance and maintaining a robust property information framework, including sensor data where relevant.
  • Developing and improving asset information systems, ensuring they’re configured and integrated effectively, secure, and aligned with organisational planning.
  • Driving high standards of data gathering, validation, QA, and audit readiness across all property records.
  • Producing and presenting validated reports, KPIs, portfolio insights, statutory returns, and modelling support for investment and scenario planning.
  • Overseeing the review and upkeep of investment / divestment models so they accurately reflect live and completed works.
  • Managing contractors and supporting the implementation of a new asset management system replacement project.
  • Coaching, motivating, and developing a multi-disciplinary team to sustain high performance and continuous improvement.
What we’re looking for

This role suits a confident data leader who can blend technical depth with stakeholder influence. You’ll bring :

Experience & technical capability
  • Extensive technical experience in asset / property data management.
  • Advanced skills in Power BI, Excel and data governance tools (e.g., Purview).
  • Strong database experience, ideally within asset management.
  • Proficiency in desktop / mobile GIS (ArcGIS, MapInfo). - desirable
  • A track record of building / maintaining complex datasets and producing clear, compelling reports.
  • Experience supporting modelling of investment plans / programmes using multiple data sources.
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